[Prediction of the epitopes of SARS-CoV-2 by immunoinformatics]

Objective To predict the epitopes of B cells, cytotoxic T lymphocytes (CTL), and T helper (Th) cells of SARS-CoV-2 by immunoinformatics. Methods The SARS-CoV-2 protein sequences were retrieved from NCBI database and screened, and the sequences with antigenicity ≥0.5 and amino acid number ≥100 were used for epitopes prediction. The Phyre2 server was used to predict the three-dimensional (3D) structure, the GalaxyRefine system to optimize the 3D structure, and the SWISS-MODEL system to evaluate the accuracy of the optimized structure. The CTL, Th cells, and sequential B-cell antigen peptide prediction was based on the sequences of proteins, and the structural B-cell antigen peptide prediction on the 3D structures of proteins. The cytotoxic T lymphocyte (CTL) and Th cell epitopes of SARS-CoV-2 were predicted by the IEDB database. The sequential B-cell antigen peptide prediction and the structural B-cell antigen peptide prediction were performed by BepiPred-2.0: Sequential B-Cell Epitope Predictor and ElliPro-a structure-based tool for the prediction of epitopes, respectively. Results Twenty seven SARS-CoV-2 protein sequences were obtained from the NCBI database. After removing the proteins with antigenicity <0.5 and amino acid number <100, nine proteins were selected for antigen peptide prediction. Finally, 24 epitopes from CTLs, 20 epitopes from Th cells, and 12 sequential epitopes and 16 structural epitopes from B cells were obtained. Conclusion The epitopes obtained can be used for developing multi-epitope SARS-CoV-2 vaccines. Compared with epitopes that only target a single protein, multi-target epitopes have stronger immunogenicity. These epitopes have certain reference value for the development of SARS-CoV-2 vaccine.